Edge topography measurement technology is vital in many engineering applications such as cutting tool inspection, photomask inspection, or corrosive wear inspection. Although those applications require high-level sharpness or smoothness of the edges to achieve their needs, there is little measurement and inspection technology available. Most of the current surface metrology and inspection technology is primarily focused on planar surface characterization [1-3], and sometimes indirect methods such as measuring the cutting force or acceleration to interpret tool wear propagation during the machining process are used [4]. This paper presents the enhanced knife-edge interferometry (KEI) that measures optical scattering behaviors that originated from the edge. KEI utilizes the optical interference of incident light and scattered light at the edge and produces the fringe patterns proportional to edge quality [5-7]. Analysis of such fringe patterns enables monitoring edge quality. We recently improved KEI performance by shaping the beam with the objective lens (4×, 10×). The incident plane wave was turned into a spherical wave by the objective lens, and the spherical wave and the diffracted wave at the edge interfered. As a result, the strong interference effect was observed, and over 3 times fringe patterns were obtained compared to the interference results of no objective case. The enhanced KEI was employed for edge quality inspection of sharp edges (razor blade), cutting tools, and photomask.
more »
« less
REVIEW OF KEI METHOD-BASED DIMENSIONAL MEASUREMENT, POSITIONING CONTROL AND PART INSPECTION
This paper reviews knife-edge interferometry (KEI) capable
of inspection and metrology for various engineering
applications, including displacement measuring sensors for
dynamic system controls and edge quality of the parts, such as
cutting tools, corrosive blades, and photomask patterns. This
paper includes the modeling, design, and data analysis of KEI.
With the expanding market of manufacturing industries, edge
topography and instrumentation technology become more and
more vital to industrial manufacturing-related applications such
as cutting tool wear inspection, photomask edge roughness
determination, and edge corrosion propagation monitoring. Due
to the limitation of measurement requirements like non-contact
(photomask inspection), in-situ (cutting tool inspection), and
real-time (corrosion propagation monitoring), there are only a
few methods available in the market above, and those methods
are based on post-processing. The KEI is capable of on-machine
measurements, especially for the nanopositioning systems,
providing a large working range and positioning accuracy
compared with the conventional displacement sensor. This
review addresses the current and future KEI technology. Here,
including the theoretical approaches to KEI, this review details
the data analy
more »
« less
- Award ID(s):
- 1855473
- NSF-PAR ID:
- 10334501
- Date Published:
- Journal Name:
- Manufacturing Engineering and Science Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
20‐1: Invited Paper: Rethinking Display Requirements for Esports and High Interactivity ApplicationsMedia technology is continuing its transition from passive streaming to participatory interactive experiences, including well‐known applications such as web browsing, video conferencing and gaming, as well as emerging and more demanding uses like AR/MR/VR and esports. How should display traits such as latency, refresh rate and size change to meet this trend? We review recent studies from NVIDIA Research and others on requirements for esports as the cutting edge of this trend toward interactivity, and discuss the studies’ implications for other interactive applications.more » « less
-
Line-edge roughness (LER) characterization is vital in the semiconductor industry to this day. This paper presents an EKEI (enhanced knife edge interferometry)-based system for photomask LER characterization. From the given EKEI-based system, the LER on the photomask pattern can be characterized. In this paper, the Fresnel (F) number-based geometrical optical model was developed for the LER-induced edge diffraction fringe simulation. The LER here was defined by three times the standard deviation of the edge profile on the photomask. Periodic rectangular functions were employed to characterize LER effects on the diffraction fringe patterns in simulation. The simulation-generated fringe pattern was then analyzed by cross-correlation. From the simulation result, the fringe pattern will get attenuated when adding the LER onto the line edge profile. Once the LER value increases, some of the high-order fringes vanish. A negative correlation between the similarity and the LER value was discovered. From the F number-based simulation model, the real photomask decorated with different LER values was designed and fabricated. After the photomask writing process, we used the EKEI system to scan the LER-programmed pattern for photomask LER characterization. By using the cross-correlation, the same trend was found in the experiment and simulation results. The fringe pattern from the edge was attenuated while the LER was added to the edge. The geometrical-based simulation and analysis model for photomask LER characterization was validated. From the simulation results, the fringe pattern from the edge was attenuated when adding LER on the edge. The experiment results show good agreement with the simulation ones. In sum, the proposed EKEI-based system has great potential to be utilized for on-machine photomask LER characterization and those defect inspection. The F number-based geometrical optical model also has the potential for diffraction-free pattern design and analysis.more » « less
-
more » « less
Abstract Lithium‐ion batteries (LIBs) have significantly impacted the daily lives, finding broad applications in various industries such as consumer electronics, electric vehicles, medical devices, aerospace, and power tools. However, they still face issues (i.e., safety due to dendrite propagation, manufacturing cost, random porosities, and basic & planar geometries) that hinder their widespread applications as the demand for LIBs rapidly increases in all sectors due to their high energy and power density values compared to other batteries. Additive manufacturing (AM) is a promising technique for creating precise and programmable structures in energy storage devices. This review first summarizes light, filament, powder, and jetting‐based 3D printing methods with the status on current trends and limitations for each AM technology. The paper also delves into 3D printing‐enabled electrodes (both anodes and cathodes) and solid‐state electrolytes for LIBs, emphasizing the current state‐of‐the‐art materials, manufacturing methods, and properties/performance. Additionally, the current challenges in the AM for electrochemical energy storage (EES) applications, including limited materials, low processing precision, codesign/comanufacturing concepts for complete battery printing, machine learning (ML)/artificial intelligence (AI) for processing optimization and data analysis, environmental risks, and the potential of 4D printing in advanced battery applications, are also presented.
-
more » « less
This paper presents a novel noncontact measurement and inspection method based on knife-edge diffraction theory for corrosive wear propagation monitoring at a sharp edge. The degree of corrosion on the sharp edge was quantitatively traced in process by knife-edge interferometry (KEI). The measurement system consists of a laser diode, an avalanche photodiode, and a linear stage for scanning. KEI utilizes the interferometric fringes projected on the measurement plane when the light is incident on a sharp edge. The corrosion propagation on sharp edges was characterized by analyzing the difference in the two interferometric fringes obtained from the control and measurement groups. By using the cross-correlation algorithm, the corrosion conditions on sharp edges were quantitatively quantified into two factors: lag and similarity for edge loss and edge roughness, respectively. The KEI sensor noise level was estimated at 0.03% in full scale. The computational approach to knife-edge diffraction was validated by experimental validation, and the computational error was evaluated at less than 1%. Two sets of razor blades for measurement and control groups were used. As a result, the lag will be increased at an edge loss ratio of 1.007/µm due to the corrosive wear, while the similarity will be decreased at a ratio of
with respect to edge roughness change. Experimental results showed a good agreement with computational results.
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
